HSH Intelligence GitHub Code Corpus Sample: 5,000 Records

HSH Intelligence provides a 5,000-record sample of its GitHub Code AI Training Corpus. The full corpus contains 5.6 TB of source code from top-tier public GitHub repositories, comprising over 211 million files and 7.05 billion lines across 14 production languages. The sample is described as curated and production-grade, engineered for large language model training and code understanding research.

Use Cases

• Fine-tuning code generation models based on source code from top-tier repositories.
• Training models for code understanding research based on a multi-language corpus.
• Evaluating language model performance on code-related tasks using a curated sample.
• Studying patterns and structures in production-grade source code across 14 languages.

Strengths

• Sample is curated and described as production-grade.
• Full corpus scale is substantial: 5.6 TB, 211 million+ files, 7.05 billion lines.
• Source code is sourced from top-tier public GitHub repositories.
• Corpus spans 14 production languages.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count for the sample is unknown, which may limit suitability assessment.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

HSH-Intelligence

Collection Method

Curated from top-tier public GitHub repositories.

Freshness

Last updated 2026-05-07 12:05:16; freshness should be verified.